Real World Natural Language Processing
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Real World Natural Language Processing
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Author : Masato Hagiwara
language : en
Publisher: Simon and Schuster
Release Date : 2021-12-14
Real World Natural Language Processing written by Masato Hagiwara and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-14 with Computers categories.
Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! The field of Natural language processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assitants, text generation and more. "Real-world natural language processing" shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you'll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you'll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process.
Real World Natural Language Processing
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Author : Masato Hagiwara
language : en
Publisher: Manning
Release Date : 2021-12-14
Real World Natural Language Processing written by Masato Hagiwara and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-14 with Computers categories.
Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. In Real-world Natural Language Processing you will learn how to: Design, develop, and deploy useful NLP applications Create named entity taggers Build machine translation systems Construct language generation systems and chatbots Use advanced NLP concepts such as attention and transfer learning Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you’ll explore the core tools and techniques required to build a huge range of powerful NLP apps, including chatbots, language detectors, and text classifiers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! Th e field of Natural Language Processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assistants, text generation, and more. About the book Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you’ll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you’ll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process. What's inside Design, develop, and deploy useful NLP applications Create named entity taggers Build machine translation systems Construct language generation systems and chatbots About the reader For Python programmers. No prior machine learning knowledge assumed. About the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009. He has interned at Google and Microsoft Research, and worked at Duolingo as a Senior Machine Learning Engineer. He now runs his own research and consulting company. Table of Contents PART 1 BASICS 1 Introduction to natural language processing 2 Your first NLP application 3 Word and document embeddings 4 Sentence classification 5 Sequential labeling and language modeling PART 2 ADVANCED MODELS 6 Sequence-to-sequence models 7 Convolutional neural networks 8 Attention and Transformer 9 Transfer learning with pretrained language models PART 3 PUTTING INTO PRODUCTION 10 Best practices in developing NLP applications 11 Deploying and serving NLP applications
Practical Natural Language Processing
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Author : Sowmya Vajjala
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-06-17
Practical Natural Language Processing written by Sowmya Vajjala and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Computers categories.
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Natural Language Processing With Python
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Author : Ryan Lofton
language : en
Publisher: Independently Published
Release Date : 2025-08-02
Natural Language Processing With Python written by Ryan Lofton and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-02 with Computers categories.
Natural Language Processing with Python: Build Real-World NLP Applications Using NLTK, spaCy, and Transformers This hands-on guide takes you on a practical journey into the world of Natural Language Processing (NLP) using Python. Whether you're a beginner or looking to enhance your skills, this book equips you with the tools and techniques to build real-world NLP applications using the most popular libraries: NLTK, spaCy, and Hugging Face Transformers. From foundational text processing to cutting-edge deep learning models, you'll learn how to preprocess, analyze, and understand text in meaningful ways. Covering everything from tokenization and named entity recognition to fine-tuning transformer models like BERT and GPT, the book blends theory with real implementation. You'll work through complete projects such as text classification, sentiment analysis, question answering, and language generation making it easy to apply what you learn directly to real use cases. Natural Language Processing with Python bridges the gap between theory and practice by guiding readers through essential NLP workflows using three powerful libraries. You'll master the basics with NLTK, streamline processes with spaCy, and tap into state-of-the-art AI using Hugging Face Transformers. The book is structured to build your confidence from the ground up starting with core preprocessing tasks and culminating in the deployment of modern NLP applications. Key Features of This Book: Step-by-step tutorials for practical NLP tasks using real datasets In-depth exploration of NLTK, spaCy, and Transformers Full projects on text classification, summarization, and more Clear explanations with annotated code examples Guidance on deploying NLP models with FastAPI or Flask Best practices for evaluating model performance and mitigating bias This book is ideal for Python developers, data scientists, machine learning enthusiasts, and students who want to learn NLP through hands-on projects. No prior experience with NLP is required, but a basic understanding of Python will help you get the most out of the book. Ready to unlock the power of language with code? Natural Language Processing with Python gives you the skills and confidence to build your own NLP applications from scratch. Start your NLP journey today and turn messy text into smart insights!
Natural Language Processing With Python
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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-01-16
Natural Language Processing With Python written by Cuantum Technologies LLC and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-16 with Computers categories.
Learn NLP with Python through practical exercises, advanced topics like transformers, and real-world projects such as chatbots and dashboards. A comprehensive guide for mastering NLP techniques. Key Features A comprehensive guide to processing, analyzing, and modeling human language with Python Real-world projects that reinforce NLP concepts, including chatbot design and sentiment analysis Foundational and advanced NLP techniques for practical applications in diverse domains Book DescriptionEmbark on a comprehensive journey to master natural language processing (NLP) with Python. Begin with foundational concepts like text preprocessing, tokenization, and key Python libraries such as NLTK, spaCy, and TextBlob. Explore the challenges of text data and gain hands-on experience in cleaning, tokenizing, and building basic NLP pipelines. Early chapters provide practical exercises to solidify your understanding of essential techniques. Advance to sophisticated topics like feature engineering using Bag of Words, TF-IDF, and embeddings like Word2Vec and BERT. Delve into language modeling with RNNs, syntax parsing, and sentiment analysis, learning to apply these techniques in real-world scenarios. Chapters on topic modeling and text summarization equip you to extract insights from data, while transformer-based models like BERT take your skills to the next level. Each concept is paired with Python-based examples, ensuring practical mastery. The final chapters focus on real-world projects, such as developing chatbots, sentiment analysis dashboards, and news aggregators. These hands-on applications challenge you to design, train, and deploy robust NLP solutions. With its structured approach and practical focus, this book equips you to confidently tackle real-world NLP challenges and innovate in the field.What you will learn Clean and preprocess text data using Python effectively Master tokenization techniques for words, sentences, and characters Build robust NLP pipelines with feature engineering methods Implement sentiment analysis with machine learning models Perform topic modeling using LDA, LSA, and other algorithms Develop chatbots and dashboards for real-world applications Who this book is for This book is ideal for students, researchers, and professionals in machine learning, data science, and artificial intelligence who want to master NLP. Beginners will benefit from the step-by-step introduction to text processing and feature engineering, while experienced practitioners can explore advanced topics like transformers and real-world projects. Basic knowledge of Python and familiarity with programming concepts are recommended to fully utilize the content. Enthusiasts with a passion for language technology will also find this guide valuable for building practical NLP applications.
Natural Language Processing In Action
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Author : Hannes Hapke
language : en
Publisher: Simon and Schuster
Release Date : 2019-03-16
Natural Language Processing In Action written by Hannes Hapke and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Computers categories.
Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)
Hands On Python Natural Language Processing
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Author : Aman Kedia
language : en
Publisher:
Release Date : 2020-06-26
Hands On Python Natural Language Processing written by Aman Kedia and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-26 with Computers categories.
This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples
Natural Language Processing In Real World Systems
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Author : Dr.Govinda Patil
language : en
Publisher: SK Research Group of Companies
Release Date : 2025-11-05
Natural Language Processing In Real World Systems written by Dr.Govinda Patil and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-05 with Computers categories.
Dr.Govinda Patil, Assistant Professor, Department of Computer Science, Medicaps University, Indore, Madhya Pradesh, India. Dr.Vivek Chaplot, Professor, Department of Computer Science, Bhupal Nobles’ University, Udaipur, Rajasthan, India.
Mastering Natural Language Processing Using Python
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Author : Dr. Goonjan Jain
language : en
Publisher: Sultan Chand & Sons
Release Date : 2025-02-01
Mastering Natural Language Processing Using Python written by Dr. Goonjan Jain and has been published by Sultan Chand & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-01 with Computers categories.
This book is a comprehensive guide to Natural Language Processing (NLP), designed for both beginners and advanced learners. Whether you're just starting or looking to refine your skills, this book takes you through every aspect of NLP – from the basics of text processing to cutting-edge machine learning techniques used in NLP today. It combines theoretical foundations with practical examples using Python, making complex NLP concepts accessible and actionable. The book is rich with practical exercises, hands-on Python code snippets, and visual aids, ensuring that readers not only understand the concepts but also see how they apply in real-world scenarios. By the end of the book, readers will be proficient in using NLP libraries and will have a clear understanding of how to implement NLP solutions in Python.
Advanced Natural Language Processing With Tensorflow 2
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Author : Ashish Bansal
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-04
Advanced Natural Language Processing With Tensorflow 2 written by Ashish Bansal and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-04 with Computers categories.
One-stop solution for NLP practitioners, ML developers, and data scientists to build effective NLP systems that can perform real-world complicated tasks Key FeaturesApply deep learning algorithms and techniques such as BiLSTMS, CRFs, BPE and more using TensorFlow 2Explore applications like text generation, summarization, weakly supervised labelling and moreRead cutting edge material with seminal papers provided in the GitHub repository with full working codeBook Description Recently, there have been tremendous advances in NLP, and we are now moving from research labs into practical applications. This book comes with a perfect blend of both the theoretical and practical aspects of trending and complex NLP techniques. The book is focused on innovative applications in the field of NLP, language generation, and dialogue systems. It helps you apply the concepts of pre-processing text using techniques such as tokenization, parts of speech tagging, and lemmatization using popular libraries such as Stanford NLP and SpaCy. You will build Named Entity Recognition (NER) from scratch using Conditional Random Fields and Viterbi Decoding on top of RNNs. The book covers key emerging areas such as generating text for use in sentence completion and text summarization, bridging images and text by generating captions for images, and managing dialogue aspects of chatbots. You will learn how to apply transfer learning and fine-tuning using TensorFlow 2. Further, it covers practical techniques that can simplify the labelling of textual data. The book also has a working code that is adaptable to your use cases for each tech piece. By the end of the book, you will have an advanced knowledge of the tools, techniques and deep learning architecture used to solve complex NLP problems. What you will learnGrasp important pre-steps in building NLP applications like POS taggingUse transfer and weakly supervised learning using libraries like SnorkelDo sentiment analysis using BERTApply encoder-decoder NN architectures and beam search for summarizing textsUse Transformer models with attention to bring images and text togetherBuild apps that generate captions and answer questions about images using custom TransformersUse advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest DeepNLP modelsWho this book is for This is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. The readers who can benefit the most from this book include intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques and professionals who already use TensorFlow/Python for purposes such as data science, ML, research, analysis, etc.